DeepMIMO: A Generic Deep Learning Dataset for Millimeter Wave and Massive MIMO Applications

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2013

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E. G. Larsson, O. Edfors, F. Tufvesson, and T. L. Marzetta, “Massive mimo for next generation wireless systems,” IEEE communications magazine , vol. 52, no. 2, pp. 186–195, 2014

2014

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A. Alkhateeb, J. Mo, N. Gonzalez-Prelcic, and R. Heath, “MIMO precoding and combining solutions for millimeter-wave systems,” IEEE Communications Magazine, , vol. 52, no. 12, pp. 122–131, Dec. 2014

2014

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F. Boccardi, R. Heath, A. Lozano, T. Marzetta, and P. Popovski, “Five disruptive technology directions for 5G,” IEEE Communications Magazine , vol. 52, no. 2, pp. 74–80, Feb. 2014

2014

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V. Jungnickel, K. Manolakis, W. Zirwas, B. Panzner, V. Braun, M. Lossow, M. Sternad, R. Apelfrojd, and T. Svensson, “The role of small cells, coordinated multipoint, and massive mimo in 5g,” IEEE Communications Magazine , vol. 52, no. 5, pp. 44–51, 2014

2014

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Q. Li, H. Shirani-Mehr, T. Balercia, A. Papathanassiou, G. Wu, S. Sun, M. K. Samimi, and T. S. Rappaport, “Validation of a geometry-based statistical mmwave channel model using ray-tracing simulation,” in 2015 IEEE 81st Vehicular Technology Conference (VTC Spring) , May 2015, pp. 1–5

2015

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R. W. Heath, N. Gonzlez-Prelcic, S. Rangan, W. Roh, and A. M. Sayeed, “An overview of signal processing techniques for millimeter wave MIMO systems,” IEEE Journal of Selected Topics in Signal Processing , vol. 10, no. 3, pp. 436–453, April 2016

2016

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E. Björnson, E. G. Larsson, and M. Debbah, “Massive mimo for maximal spectral efficiency: How many users and pilots should be allocated?” IEEE Transactions on Wireless Communications , vol. 15, no. 2, pp. 1293–1308, 2016

2016

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S. Mumtaz, J. Rodriguez, and L. Dai, MmWave Massive MIMO: A Paradigm for 5G . Academic Press, 2016

2016

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S. Wu, S. Hur, K. Whang, and M. Nekovee, “Intra-cluster characteristics of 28 ghz wireless channel in urban micro street canyon,” in 2016 IEEE Global Communications Conference (GLOBECOM) , Dec 2016, pp. 1–6

2016

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V. Va, J. Choi, T. Shimizu, G. Bansal, and R. W. Heath, “Inverse multipath fingerprinting for millimeter wave v2i beam alignment,” IEEE Transactions on Vehicular Technology , vol. PP, no. 99, pp. 1–1, 2017

2017

Cited alongside, same era.

A. Alkhateeb, I. Beltagy, and S. Alex, “Machine learning for reliable mmwave systems: Blockage prediction and proactive handoff,” in IEEE GlobalSIP, arXiv preprint arXiv:1807.02723 , 2018

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2018

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F. B. Mismar and B. L. Evans, “Partially blind handovers for mmwave new radio aided by sub-6 ghz lte signaling,” in 2018 IEEE International Conference on Communications Workshops (ICC Workshops) , May 2018, pp. 1–5

2018

Later among the works it cites.

A. Klautau, P. Batista, N. G. Prelcic, Y. Wang, and R. W. Heath, “5G MIMO data for machine learning: Application to beam-selection using deep learning,” in Inf. Theory and Appl. Workshop (ITA) , Feb 2018, pp. 1–6

2018

Later among the works it cites.

C.-K. Wen, W.-T. Shih, and S. Jin, “Deep learning for massive mimo csi feedback,” IEEE Wireless Communications Letters , 2018

2018

Later among the works it cites.